Abstracts:In this letter, a bilevel linear programming model is proposed to reveal the severe cyber-attack scheme in economic dispatch. By using this model, not only many branches including the targeted ones can be overloaded, but also the total loadings of all overloaded branches are maximized. This is a serious attack, since large power flows will be redistributed and it could further cause overloaded branches if those attacked branches are tripped due to overloading. Simulations on the IEEE 57-bus system show that the proposed model can successfully overload many branches including the targeted ones and maximize the total loadings of all overloaded branches.

Abstracts:An increased number of microgrids (MGs) will exist in future active distribution systems (ADSs); however, these MGs belong to multiple operators and cannot simply be controlled as a public grid in the electricity market environment. For multi-MGs (MMGs) which have multiple coexisting beneficiaries, it will be unfeasible to realize a cooperative control among them. Hence, we propose a game theoretic non-cooperative distributed coordination control (NCDCC) scheme to address multi-operator energy trading and facilitate a powerful control structure for MMGs. The proposed NCDCC coordinates the individual benefits of each MG and achieves a global objective based on differential game theory. Furthermore, it simplifies the implementation of many ADS control functions, including global coordination, local autonomy, and self-healing, by reconsidering an ADS as MMGs and every MG as an agent. Moreover, the NCDCC reduces the control dimension and number of agents by obviating the requirements for a central controller and complex communication topologies. This article investigates the effectiveness, adaptability, and fairness of this scheme by means of several representative cases studies.

Abstracts:Most current customer baseline load (CBL) estimation methods for incentive-based demand response (DR) rely heavily on historical data and are unable to adapt to the cases when the load patterns (LPs) in the DR event day are not similar enough to those in non-DR days. After the error generation mechanism of current methods is revealed, a synchronous pattern matching principle-based residential CBL estimation approach without historical data requirement is proposed. All customers are split into DR and CONTROL group, including DR participants and non-DR customers, respectively. First, all CONTROL group customers are clustered into several non-overlapping clusters according to LPs similarity in the DR event day. Second, each DR participant is matched to the most similar cluster in the CONTROL group according to the similarity between its load curve segments in DR event day, excluding DR part and cluster centroids. Third, the CBL of each DR participant is estimated with an optimized weight combination method using the load data within the DR event period of all the customers in the very matching cluster in the CONTROL group. A comparison with five well-known CBL estimation methods using a dataset of 736 residential customers indicates that the proposed approach has better overall performance than other current CBL estimation methods.

Abstracts:Competitive transactions resulting from recent restructuring of the electricity market, have made achieving a precise and reliable load forecasting, especially probabilistic load forecasting, an important topic. Hence, this paper presents a novel hybrid method of probabilistic electricity load forecasting, including generalized extreme learning machine for training an improved wavelet neural network, wavelet preprocessing and bootstrapping. In the proposed method, the forecasting model and data noise uncertainties are taken into account while the output of the model is the load probabilistic interval. In order to validate the method, it is implemented on the Ontario and Australian electricity markets data. Also, in order to remove the influence of model parameters and data on performance validation, Friedman and post-hoc tests, which are non-parametric tests, are applied to the proposed method. The results demonstrate the high performance, accuracy, and reliability of the proposed method.

Abstracts:This paper presents an expert system (ES) based on decoupled power/current decomposition and the <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>-nearest neighbor pattern recognition method to identify and choose the correct mitigation solution for power quality improvement in three-phase ac microgrids under non-sinusoidal current and voltage operations. By using power/current terms, load conformity factors and a <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>-nearest neighbor classifier, the proposed ES achieved 99.98&#x0025; classification accuracy. Simulation studies were carried out in a PSCAD/EMTDC environment, where the IEEE 13-bus feeder test system was in a grid connected microgrid mode. The obtained results indicate that the proposed ES is robust and able to easily select an appropriate/adequate compensation solution.

Abstracts:The risk of cascading outages is often associated with overloading. As a result of electrical short circuits, protective relaying picks up the faults and electrically disconnects overloaded transmission lines through circuit breakers. With similar disturbance and implication, disruptive switching cyberattacks in one or more compromised substations can initiate such events that will aggravate system&#x2019;s operating conditions, leading to a widespread blackout. This paper proposes an extended enumeration of substation outages that excludes the overloaded lines from a power flow model. First, the exhaustive combination which starts from the initial combination size <inline-formula> <tex-math notation="LaTeX">${k=1}$ </tex-math></inline-formula> is enumerated searching for nonconvergent solutions of the hypothesized contingencies associated with the outages of single or more substations. The depth <inline-formula> <tex-math notation="LaTeX">${k=S'}$ </tex-math></inline-formula> is the level of contingencies which determines when the evaluation will halt. Each combination is then integrated with the overloaded effect that de-energizes transmission lines under the hypothesized scenarios. Nonconvergent solutions on both attack and overloading are carried to the next level of enumerations. This may include islanding that splits a system into multiple areas. The proposed power flow verification is validated using IEEE test cases as well as evaluation of parallel computing to determine its effectiveness of nonconvergent enumeration within a reasonable timeframe.

Abstracts:Inverter voltage control techniques, including Volt-Watt and Volt-VAR, have been developed to support higher penetration integration of photovoltaic (PV) generation. These techniques typically focus on voltage regulation as measured at the point of common coupling (PCC). Implementing voltage control with distributed inverters within a low voltage network is challenging due to voltage rise between the PCC and the electrical connection point (ECP). This paper proposes a voltage correction and control method for distributed PV microinverters in a low voltage network by utilizing readily available data measurements, i.e., voltage and power at the ECP of inverters. It is shown that this method could reduce unnecessary PV microinverter tripping and power curtailment while supporting voltage control schemes at the PCC. Test results are provided from simulation-only scenarios and a power-hardware-in-the-loop test platform.

Abstracts:Solar power forecasting improvements are mainly evaluated by statistical and economic metrics, and the practical reliability benefits of these forecasting enhancements have not yet been well quantified. This paper aims to quantify reliability benefits from solar power forecasting improvements. To systematically analyze the relationship between solar power forecasting improvements and reliability performance in power system operations, an expected synthetic reliability (ESR) metric is proposed to integrate multiple state-of-the-art independent reliability metrics. The absolute value and standard deviation of area control errors (ACEs), and the North American Electric Reliability Corporation Control Performance Standard 2 (CPS2) score are calculated through a multi-timescale scheduling simulation, including the day-ahead unit commitment, real-time unit commitment, real-time economic dispatch, and automatic generation control sub-models. The absolute ACE in energy, CPS2 violations, CPS2 score, and standard deviation of the raw ACE are all calculated and combined as the ESR metric. Numerical simulations show that the reliability benefits of multi-timescale power system operations are significantly increased due to the improved solar power forecasts.

Abstracts:The purpose of this paper is to explore the applicability of linear time-invariant dynamical systems with polytopic uncertainty for modeling and control of islanded dc microgrids under plug-and-play (PnP) functionality of distributed generations (DGs). We develop a robust decentralized voltage control framework to ensure robust stability and reliable operation for islanded dc microgrids. The problem of voltage control of islanded dc microgrids with PnP operation of DGs is formulated as a convex optimization problem with structural constraints on some decision variables. The proposed control scheme offers several advantages including decentralized voltage control with no communication link, transient stability/performance, PnP capability, scalability of design, applicability to microgrids with general topology, and robustness to microgrid uncertainties. The effectiveness of the proposed control approach is evaluated through simulation studies carried out in MATLAB/SimPowerSystems Toolbox.

Abstracts:With the penetration of renewable energy, the power quality (PQ) becomes the important issue for operation stability of power system. The efficient monitoring mechanism for different multiple PQ disturbances is the fundamental infrastructure for modernization of power system. However, the diverse PQ signals result in numerous analysis techniques and make the integration of PQ monitoring difficult. To resolve the above-mentioned problem, the Prony-based PQ analysis mechanism is proposed in this paper. The commonly seen PQ disturbances, such as the fundamental frequency deviation, harmonics, interharmonics, voltage fluctuations (flickers), and PQ events, can be easily analyzed and detected with Prony-based technique and integrated for the design of monitoring system. The performance of proposed analysis mechanism can be verified by the implementation in the Pingtung ac microgrid of Taiwan.